Identifying hotspots for rare species under climate change scenarios: improving saproxylic beetle conservation in Italy

被引:28
作者
Della Rocca, Francesca [1 ]
Bogliani, Giuseppe [1 ]
Breiner, Frank Thomas [2 ,3 ]
Milanesi, Pietro [4 ]
机构
[1] Univ Pavia, Dept Earth & Environm Sci, Via Ferrata 1, I-27100 Pavia, Italy
[2] Univ Lausanne, Dept Ecol & Evolut, CH-1015 Lausanne, Switzerland
[3] Swiss Fed Res Inst WSL, Zurcherstr 111, CH-8903 Birmensdorf, Switzerland
[4] Swiss Ornithol Inst, Seerose 1, CH-6204 Sempach, Switzerland
关键词
Climate change; Ensemble of small models; Gap analysis; Protected areas; Saproxylic conservation; Species distribution models; Species richness; PROTECTED AREAS; HIGH-RESOLUTION; DISTRIBUTIONS; DISPERSAL; BIODIVERSITY; TEMPERATURE; DIVERSITY; RICHNESS; MICROCLIMATE; MANAGEMENT;
D O I
10.1007/s10531-018-1670-3
中图分类号
X176 [生物多样性保护];
学科分类号
090705 ;
摘要
Our aim is to model rare species (with few occurrences) but modelling the distribution of species with few occurrence data and many predictor variables leads to model overfitting. Thus, we use the recently developed ensemble of small models, which showed high predictive accuracy in modelling the distribution of rare species to estimate the current and future distribution of 56 rare (and endangered) saproxylic beetle species. Thus, we stacked predictions from individual species distribution models to derive rare species richness. We used current and five future general circulation models and three representative concentration pathways to test whether the distribution of hotspots for rare species shifts due to climate change under different future scenarios. Moreover, we verified the representativeness of existing protected area systems under future climate conditions in Italy. Specifically, we identified potential hotspots for rare species richness through a cumulative relative frequency distribution function. The current surface covered by hotspots is 50.4% of the study area corresponding to 151,223km(2) (mainly from central to northern Italy). Currently, only 35,124km(2) of rare saproxylic hotspots are covered by protected areas (PAs) and they will decrease by about 2-72% in 2070 depending on the future scenarios considered. Our results confirmed that the shift of the distribution of hotspots for rare species might occur due to climate change under different future scenarios and that the existing PAs system would be inadequate for assuring the conservation of rare saproxylic beetles in Italy under current and future climate conditions.
引用
收藏
页码:433 / 449
页数:17
相关论文
共 88 条
[1]   Matching species with reserves -: uncertainties from using data at different resolutions [J].
Araújo, MB .
BIOLOGICAL CONSERVATION, 2004, 118 (04) :533-538
[2]   Climate change threatens European conservation areas [J].
Araujo, Miguel B. ;
Alagador, Diogo ;
Cabeza, Mar ;
Nogues-Bravo, David ;
Thuiller, Wilfried .
ECOLOGY LETTERS, 2011, 14 (05) :484-492
[3]  
Audisio P., 2014, LISTA ROSSA IUCN COL, P132
[4]   Error and uncertainty in habitat models [J].
Barry, Simon ;
Elith, Jane .
JOURNAL OF APPLIED ECOLOGY, 2006, 43 (03) :413-423
[5]   Frequency distribution curves and the identification of hotspots: response to comments [J].
Bartolino, Valerio ;
Maiorano, Luigi ;
Colloca, Francesco .
POPULATION ECOLOGY, 2011, 53 (04) :603-604
[6]   A frequency distribution approach to hotspot identification [J].
Bartolino, Valerio ;
Maiorano, Luigi ;
Colloca, Francesco .
POPULATION ECOLOGY, 2011, 53 (02) :351-359
[7]   The ecological niche and distribution of Neanderthals during the Last Interglacial [J].
Benito, Blas M. ;
Svenning, Jens-Christian ;
Kellberg-Nielsen, Trine ;
Riede, Felix ;
Gil-Romera, Graciela ;
Mailund, Thomas ;
Kjaergaard, Peter C. ;
Sandel, Brody S. .
JOURNAL OF BIOGEOGRAPHY, 2017, 44 (01) :51-61
[8]   Regional temperature variability in the European Alps:: 1760-1998 from homogenized instrumental time series [J].
Böhm, R ;
Auer, I ;
Brunetti, M ;
Maugeri, M ;
Nanni, T ;
Schöner, W .
INTERNATIONAL JOURNAL OF CLIMATOLOGY, 2001, 21 (14) :1779-1801
[9]   Evaluating resource selection functions [J].
Boyce, MS ;
Vernier, PR ;
Nielsen, SE ;
Schmiegelow, FKA .
ECOLOGICAL MODELLING, 2002, 157 (2-3) :281-300
[10]   Selecting from correlated climate variables: a major source of uncertainty for predicting species distributions under climate change [J].
Braunisch, Veronika ;
Coppes, Joy ;
Arlettaz, Raphael ;
Suchant, Rudi ;
Schmid, Hans ;
Bollmann, Kurt .
ECOGRAPHY, 2013, 36 (09) :971-983